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Use of Data-Mining for Non-Invasive Harmonic Signature Recognition in Micro-Grids: A Preliminary Approach applied to Residential Areas with PV Converters
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| Author(s) |
Daniel SIEMASZKO |
| Abstract |
The future of distribution networks tends more and more to include computational power, embedded intelligence and smart metering on the high voltage level as well as the low voltage micro-grids. Several hardware solutions were developed to implement the so-called smart grids with measurement devices delivering data about the state of networks on various levels. This work introduces the use of a specific electric signature based on harmonic response of power converters in order to be able to get information in a non-invasive manner. A simulated residential grid with several loads and PV converters has been run real-time with one micro second sampled data, for being able to retrieve information through data mining methods. |
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| Filename: | 0161-epe2017-full-15583501.pdf |
| Filesize: | 1.926 MB |
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| Type |
Members Only |
| Date |
Last modified 2018-04-17 by System |
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